Characteristics and Sources of Hourly Trace Elements in Airborne Fine Particles in Urban Beijing, China

被引:60
作者
Cui, Yang [1 ,2 ]
Ji, Dongsheng [1 ,2 ]
Chen, Hui [3 ]
Gao, Meng [4 ]
Maenhaut, Willy [5 ]
He, Jun [6 ]
Wang, Yuesi [1 ,2 ,7 ]
机构
[1] Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Atmospher Boundary Layer Phys & Atm, Beijing, Peoples R China
[2] Univ Chinese Acad Sci, Coll Earth & Planetary Sci, Beijing, Peoples R China
[3] Fudan Univ, Shanghai Key Lab Atmospher Particle Pollut & Prev, Inst Atmospher Sci, Dept Environm Sci & Engn, Shanghai, Peoples R China
[4] Harvard Univ, John A Paulson Sch Engn & Appl Sci, Cambridge, MA 02138 USA
[5] Univ Ghent, Dept Chem, Ghent, Belgium
[6] Univ Nottingham Ningbo China, Dept Chem & Environm Engn, Int Doctoral Innovat Ctr, Ningbo, Zhejiang, Peoples R China
[7] Chinese Acad Sci, Inst Urban Environm, Ctr Excellence Reg Atmospher Environm, Xiamen, Fujian, Peoples R China
关键词
POSITIVE MATRIX FACTORIZATION; RIVER DELTA REGION; SOURCE APPORTIONMENT; HEAVY-METALS; PARTICULATE MATTER; CHEMICAL-COMPOSITION; SEASONAL-VARIATION; AIR-POLLUTION; SPATIOTEMPORAL VARIATIONS; ESTIMATING UNCERTAINTY;
D O I
10.1029/2019JD030881
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
To better investigate the characteristics and sources of trace elements (TEs) in PM2.5 in urban Beijing, a 1-year hourly observation was continuously made using an online multi-element analyzer from 1 June 2016 to 31 May 2017. The average concentrations of 14 individual TEs ranged from 1.1 (V) to 900 ng/m(3) (K). The occurrence levels of most TEs of interest in Beijing were lower than those in most domestic cities, but higher than those in most foreign countries. The formation of sulfate increased with the concentrations of all studied TEs during autumn and winter. Dust, industry, biomass burning and waste incineration, vehicle emissions, coal combustion, and oil combustion were identified by the positive matrix factorization (PMF) model, which accounted for 36.3%, 10.7%, 27.1%, 13.7%, 7.6%, and 4.6%, respectively, of the total elements. All factors exhibited higher concentrations on weekends than on weekdays. Local vehicular emissions and industry contributed to the loading of TEs, but dust, biomass burning and waste incineration, coal combustion, and oil combustion from neighboring areas appeared to be dominant sources of TEs. Except for dust and industry, the four other sources of TEs were mainly located in the south and southeast areas of the sampling site. The analysis by conditional probability function and potential source contribution function showed that the distribution of the PMF sources of TEs roughly agreed with the location of the main point sources. Overall, this work provides more detailed information on the characteristics of the TEs for the scientific community and modelling work. Plain Language Summary A 1-year hourly observation of trace elements (TEs) was continuously made using an online multi-element analyzer in urban Beijing. The levels of most TEs of interest in Beijing were lower than those in most domestic cities of China but higher than those in most foreign countries. The formation of sulfate increased with the concentrations of all studied trace elements during autumn and winter. Six categories of sources of TEs were identified using the positive matrix factorization (PMF) model. All factors exhibited higher concentrations on weekends than on weekdays. Except for dust and industry, the four other sources of the TEs were mainly located in areas to the south and southeast of the sampling site. The analysis by conditional probability function and potential source contribution function showed that the distribution of the PMF sources of the TEs roughly agreed with the location of main point sources.
引用
收藏
页码:11595 / 11613
页数:19
相关论文
共 93 条
  • [1] Source apportionment of atmospheric urban aerosol based on weekdays/weekend variability: evaluation of road re-suspended dust contribution
    Almeida, SM
    Pio, CA
    Freitas, MC
    Reis, MA
    Trancoso, MA
    [J]. ATMOSPHERIC ENVIRONMENT, 2006, 40 (11) : 2058 - 2067
  • [2] [Anonymous], 2016, CHINESE GOVT NEWS
  • [3] [Anonymous], 2016, ATMOSPHERIC CHEM PHY
  • [4] Distribution of heavy metals in road dust along an urban-rural gradient in Massachusetts
    Apeagyei, Eric
    Bank, Michael S.
    Spengler, John D.
    [J]. ATMOSPHERIC ENVIRONMENT, 2011, 45 (13) : 2310 - 2323
  • [5] A RESIDENCE TIME PROBABILITY ANALYSIS OF SULFUR CONCENTRATIONS AT GRAND-CANYON-NATIONAL-PARK
    ASHBAUGH, LL
    MALM, WC
    SADEH, WZ
    [J]. ATMOSPHERIC ENVIRONMENT, 1985, 19 (08) : 1263 - 1270
  • [6] Beijing Municipal Bureau of Statistics, 2017, BEIJ STAT YB 2017
  • [7] Methods for estimating uncertainty in PMF solutions: Examples with ambient air and water quality data and guidance on reporting PMF results
    Brown, Steven G.
    Eberly, Shelly
    Paatero, Pentti
    Norris, Gary A.
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2015, 518 : 626 - 635
  • [8] openair - An R package for air quality data analysis
    Carslaw, David C.
    Ropkins, Karl
    [J]. ENVIRONMENTAL MODELLING & SOFTWARE, 2012, 27-28 : 52 - 61
  • [9] First long-term and near real-time measurement of trace elements in China's urban atmosphere: temporal variability, source apportionment and precipitation effect
    Chang, Yunhua
    Huang, Kan
    Xie, Mingjie
    Deng, Congrui
    Zou, Zhong
    Liu, Shoudong
    Zhang, Yanlin
    [J]. ATMOSPHERIC CHEMISTRY AND PHYSICS, 2018, 18 (16) : 11793 - 11812
  • [10] A review of biomass burning: Emissions and impacts on air quality, health and climate in China
    Chen, Jianmin
    Li, Chunlin
    Ristovski, Zoran
    Milic, Andelija
    Gu, Yuantong
    Islam, Mohammad S.
    Wang, Shuxiao
    Hao, Jiming
    Zhang, Hefeng
    He, Congrong
    Guo, Hai
    Fu, Hongbo
    Miljevic, Branka
    Morawska, Lidia
    Phong Thai
    Lam, Yun Fat
    Pereira, Gavin
    Ding, Aijun
    Huang, Xin
    Dumka, Umesh C.
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2017, 579 : 1000 - 1034